Identity verification using a kinematic memory detection technique

Abstract

We present a new method that allows the identification of false self-declared identity, based on indirect measures of the memories relating the affirmed personal details. This method exploits kinematic analysis of mouse as implicit measure of deception, while the user is answering to personal information. Results show that using mouse movement analysis, it is possible to reach a high rate of accuracy in detecting the veracity of self-declared identities. In fact, we obtained an average accuracy of 88 % in the classification of single answers as truthful or untruthful, that corresponds overall to 9.7/10 participants correctly classified as true tellers or liars. The advantage of this method is that it does not requires any knowledge about the real identity of the declarant.